Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Computers and Operations Research - Special issue: Emerging economics
Forecasting stock market movement direction with support vector machine
Computers and Operations Research
Market basket analysis in a multiple store environment
Decision Support Systems
Mining customer knowledge for product line and brand extension in retailing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Mining stock category association and cluster on Taiwan stock market
Expert Systems with Applications: An International Journal
Marking the Close analysis in Thai Bond Market Surveillance using association rules
Expert Systems with Applications: An International Journal
Discovering golden nuggets: data mining in financial application
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Hybrid genetic algorithm and association rules for mining workflow best practices
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
As the financial crisis which began in 2008 illustrates, the global stock markets influence each other. Forecasting changes in the stock market index has been an important subject for many years. In the past, data mining techniques were used to predict changes in the stock market index, but dependency of global stock market has not been seriously considered. In this paper we propose the analysis of association rule for predicting changes in the Korea Composite Stock Price Index (KOSPI) based on the time series data of various interrelated world stock market indices. According to the results of this study, the KOSPI tends to move in the same direction as the stock market indices in USA and Europe, whereas the KOSPI moves in a direction opposite to those in other East Asian countries, such as Hong Kong and Japan, which have a competitive relationship with Korea. This study is expected to facilitate effective investment decision making.